Session Information
| Session | Poster Session | | Date | Monday (2008-04-07) | | Time | 5:00 PM - 7:00 PM | | Room | Grand Terrace |
Presentation Information
| Presenter | Tara Holland | | Title | Extracting meaningful pattern information from large real-world datasets: Lessons from the EOSD Canada forest land cover | | Affiliation | Universite de Montreal | | Authors | Tara Holland, Jeffrey Cardille, Michael Wulder, Joanne White, Nicholas Coops | | Keywords | Disturbance, Fragmentation, Land cover patterns, Landscape metrics | | Presentation Type | Poster | Abstract:
Since Agenda 21 was produced at the Rio Earth Summit in 1992, international attention has been drawn to the importance of quantifying and monitoring forest loss and fragmentation. Canada’s commitment to report nationally and internationally on the state of its forests (e.g., the Montreal Process) has created the need to work with large-area land-cover data sets and to identify and utilize meaningful measures of landscape pattern for regional and national application. The recent release of the Earth Observation for Sustainable Development of Forests (EOSD) project, a joint undertaking by the Canadian Forest Service (CFS) and Canadian Space Agency, has provided the first Landsat satellite-based land-cover data set for Canada. Landscape metrics represent an important potential link between spatial patterns and ecological processes and, while their proper use requires care, they may provide the ability to extract ecological meaning from these large data sets. Despite these opportunities, several challenges remain, including questions of scale and redundancy among metrics.
We first explore the issues particular to extracting spatial meaning from large datasets built from remotely sensed data. We then review the utility of landscape metrics and the challenges associated with their application; the types of management and planning objectives that may be addressed through the use of landscape metrics, including a review of the abilities and limitations of pattern measures in prior research programs; and the novel methodologies that may be particularly useful in interpreting large data sets. Using the EOSD land-cover data as an example, we identify opportunities in which landscape pattern measures can advance ecological understanding across Canada’s forested ecozones. Specifically, we identify metrics which can be used to answer questions about how land-cover patterns interact with abiotic, biotic and human factors to influence forest disturbances.
Monitoring land-cover and forest changes, disturbance processes and spatial pattern is important for the conservation of forest landscapes and biodiversity. This research will advance Canadian forest science and landscape ecology, providing fundamental baseline information about Canada’s forests by enabling the production of new maps of landscape metrics that are suitable for comparison to a very wide range of ecological processes. |
|